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formal contract or by an informal agreement governed by trust, fairness, and reciprocity
(Schrader, 1991; von Hippel, 1987).
In view of the advantages of working together by exchanging knowledge, expertise and
ideas a further question refers to the conditions under which appropriate partners can be
found and what kind of 'distances' between heterogeneous actors have to be overcome. In
this context, Boschma (2005) distinguishes dimensions of cognitive, social, geographical,
institutional, and organizational proximity. The cognitive dimension points to proximity
between partners in terms of knowledge and capabilities that is often called technological
proximity or technological relatedness. Quite obviously, the relationship here is non-
linear in the sense that a too close proximity (not much knowledge can be exchanged)
as well as a too large distance (not much of the other's knowledge can be understood)
between the partners may not allow technical problems to be solved commonly (Cantner
and Graf, 2004, 2006; Cantner and Meder, 2007; Mowery et al., 1998). Here, the concept
of absorptive capacities of the recipient of knowledge gains importance (Cohen and
Levinthal, 1990) in the sense that those capacities are negatively related to the distance
between actors in knowledge space. Furthermore, to i nd and trust an appropriate coop-
eration partner, geographical proximity (the other is located in not too far distance)
as well as social proximity (the other is known or can easily be approached) are often
helpful, especially when we think of informal exchange or the transfer of so-called tacit
knowledge (Boschma, 2005; Breschi and Lissoni, 2003; Cantner and Meder, 2008; Singh,
2005). Finally, and referring to factors accompanying and enabling knowledge exchange,
institutional proximity refers to common habits, customs, and language, whereas organi-
zational proximity relates to the mode of exchange distinguishing between market trans-
actions, hierarchical designs, and network relations.
Besides these proximity concepts, an ei cient and durable exchange of knowledge
requires a certain degree of complementarity of partners' knowledge stocks (which to
a certain degree is related to technological or cognitive proximity) and based on that
reciprocity (not necessarily uno actu) in exchange. Additionally and obviously related
to social proximity, for knowledge exchange between actors to be repeated and/or con-
tinued, factors such as success, trust, and learning to cooperate become relevant (Gulati,
1999).
Knowledge dynamics and network development
Based on these building blocks it is possible to draw a picture of an evolving network of
innovators. The main driving mechanisms are the generation of new knowledge on the
one hand and the levelling of knowledge stocks among the actors on the other. The latter
is related to the exchange of knowledge, expertise and ideas between partners leading to
an increasing similarity of partners' knowledge stocks. The former mechanism has to do
with the main objective of cooperating in research, namely the generation of new knowl-
edge. This new knowledge has two ef ects: i rst, it advances the partners' knowledge
stocks so that they become more similar; second, their knowledge stocks become more
dissimilar compared to the knowledge stocks of actors not involved in this partnership.
Hence, looking at a group of innovative actors, the exchange of knowledge and exper-
tise leads to more homogeneous knowledge stocks whereas the (local) creation of new
knowledge tends to increase the respective heterogeneity among the network actors.
Let us now relate these two mechanisms to the dynamics of an innovator network
